Using RFT to Promote Generative Language: Understanding the HDML
Siri Ming Siri Ming

Using RFT to Promote Generative Language: Understanding the HDML

As you know, I’ve been working on some new writing for our updated and expanded text on using RFT to promote generative language (which is still very much a work in progress). One area that has emerged in RFT since we published our first handbook is the Hyper-Dimensional Multi-Level (HDML) framework (Barnes-Holmes and Harte, 2022; Barnes-Holmes et al., 2020; Barnes-Holmes et al., 2017). While the HDML framework was originally conceived as a way of capturing and organizing the variables that conceptual and experimental work in RFT has considered, and for orienting basic researchers to avenues for future work, we also find the framework helpful to organize our thinking with respect to planning intervention. Over the next few posts, I’ll describe how this conceptualization can be viewed in the context of language development and intervention in early childhood.

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Joint attention as a foundation for cooperation and language
Siri Ming Siri Ming

Joint attention as a foundation for cooperation and language

As Hart and Risley (1999) put so beautifully, language develops through cooperative interactions with others: in describing their analyses of thousands upon thousands of interactions between children and caregivers, they note that “long before the children began saying words, it was clear that they had learned the social skills fundamental to interaction” (p. 36). Within cooperative interactions, we are motivated not only by a particular outcome, but also simply by a motivation to collaborate (Tomasello, 2023). That is, the act of collaboration itself is reinforcing: collaboration may be chosen over solo opportunities to achieve a goal, and collaborative activities may be engaged in “just for fun”; if a partner stops collaborating, whether in a social game or an instrumental task, the other is likely to engage in behavior to re-engage them in the activity. Sharing the experience itself is an important source of reinforcement.

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Cooperative Contexts for Learning
Siri Ming Siri Ming

Cooperative Contexts for Learning

As I mentioned in my last post, we’ve been working on a new chapter for our upcoming comprehensive handbook, on creating cooperative contexts for learning. I have been involved in language-based early intervention in one way or another for most of my career. While much of that work has focused on precise, individualized development of VB and/or RFT-based programming to better establish flexible generative language, it has always begun with establishing a context for learning that is fun and engaging. I used to frame this as establishing “instructional control”, in the sense that we cannot provide instruction unless we have a willing learner who is happy to be with us (and you can see that in the flowchart that accompanies the first volume of myUsing RFT to Promote Generative Language handbook series with Ian Stewart and John McElwee).

This term is a great example of how words have different functions for different people based on our learning histories.

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RFT in Early Intervention: Launching the blog
Siri Ming Siri Ming

RFT in Early Intervention: Launching the blog

First, I’m so glad you’ve found me and our RFT library—thank you for joining us! I’ve written a few email newsletters over the last couple years, and wanted to share that writing in a more accessible space. I’ll be reposting some material from older emails so those of you who are new can catch up and I can have a clear commitment moving forward.

Over the last two years, Ian and John and I have been spending a lot of time working on new material for a new, comprehensive text on using RFT to promote generative language in early childhood. We’ve updated the material from our previous handbooks, and we’ll be adding considerable new material not only on more advanced relational framing repertoires, but also on establishing important early ones.

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